Potential Flood Research Articles

Investigating the flood potential of basins to locate the implementation of remedial operations in the Siah Khor watershed using VIKOR, TOPSIS, and HEC-HMS model (case study: Siah Khor watershed-Islamabad west)

Investigating the flood potential of basins to locate the implementation of remedial operations in the Siah Khor watershed using VIKOR, TOPSIS, and HEC-HMS model (case study: Siah Khor watershed-Islamabad west)

Scalability of CASCADE2001: Gis-Based Flood Risk Screening Tool to Support Watershed Master Planning

Flood risk analysis is the instrument by which floodplain and stormwater utility managers create a sound strategy and adaptation plans to reduce flood potential in their communities. As a result, there is a need to develop a flood risk screening tool to analyze watersheds and find vulnerable areas by leveraging the scientific and technological developments of the last decade to prioritize improvements. Because local municipalities are continuously challenged by the impacts of changes in precipitation and other climatic events, the screening tool needs to be scalable, while providing similar results of spatial inundation extent regardless of the scale. Likewise, the ability to perform this analysis without overwhelming limited modeling budgets is a goal for local governments who may spend large amounts of money on capital in the future to retrofit their stormwater management systems. The present study investigates the scalability of a GIS-based hydrologic-hydraulic model, CASCADE2001, to support development of watershed-based flood protection plans. The comparative analysis of the predicted flood response at three nested levels of scale were applied in south Florida to a 8-digit hydrologic unit code (HUC) level (the Caloosahatchee Watershed), a 12-digit HUC level (the Ninemile Canal Subwatershed within the Caloosahatchee Watershed), and a local municipal level (City of Clewiston, Florida within the Ninemile Canal subwatershed). The findings were that the model was scalable and the infrastructure that mattered with respect to results was driven by the scale.

Flood risk assessment of a small river with limited available data

Flood risk modeling of small watercourses is challenging when only limited input data are available. Therefore, this study assessed the flood characteristics of a small river (Tarna River: entire watershed-C, upper-VS, middle-TMS, and lower section-TOS) from 1990 to 2019. The assessment focused on modeling, model calibration, and validation using feature event-based time-series data in data-scarce environments. We showed that since the 2000s, the number of high-water levels above 250 cm, and the frequency of three flood types had increased. Flood simulation results showed the largest flooded area in the TMS section, followed by the VS, and then the TOS. The outcomes from the VS, TMS, and TOS sections did not exhibit superior performance compared to the C area. Models performed well for larger flood events, with Kling Gupta Efficiency corresponding well to NRMSE and Nash-Sutcliffe efficiency metrics. Accordingly, flood events characterized by the longest duration and high-water levels yielded outstanding results across all areas, followed by moderate flood events with good accuracy. Normal water level events exhibited significant deviations from the reference across all sections. In summary, despite the event-based modeling challenges in data-limited environments, such models can still mitigate potential flood events and improve decision-making processes.

Integration of Building Age into Flood Hazard Mapping: A Case Study of Al Ain City, United Arab Emirates

Accurate and timely information on building age is essential for mitigating the impacts of natural disasters such as earthquakes and floods. Traditional methods for collecting these data are often inefficient and costly. This study leverages remote sensing and machine learning to classify building age and integrate this information into a comprehensive flood hazard map for Al Ain City. By combining building age with elevation, topography, land use, population density, and other factors, we generated a flood hazard map that effectively identifies high-risk areas. Our results show that a significant portion of the city is has low potential for flooding (61%), while others face moderate (32%), high, or very high flood hazards. This study provides crucial information for informed decision-making regarding future urban planning, disaster management, and development strategies in Al Ain City. By identifying vulnerable buildings in advance, it supports efforts to reduce disaster risks, protect lives, and optimize resource allocation.

Enhanced oil recovery in tight reservoirs by ultrasonic-assisted CO2 flooding: Experimental study and molecular dynamics simulation

CO2-enhanced oil recovery (CO2-EOR) has attracted great attention due to its dual effects of geological carbon storage and economic benefits, but the clay swelling, asphaltene deposition and gas channeling induced by CO2 still restrict its field application. The employment of chemical agents for the purpose of improving CO2-EOR performance is often limited by the heterogeneity of reservoirs and the potential for formation damage. Physical methods, such as ultrasonic-assisted CO2 flooding, appear to offer a promising alternative for CO2-EOR and geological sequestration. This study has conducted oil displacement experiments to investigate the EOR potential of ultrasonic-assisted CO2 flooding in tight reservoirs and clarify the effects of different ultrasound parameters. The ultrasonic waves with 20 kHz of acoustic frequency, 30 W/cm2 of sound intensity, 30 min of sonication time and moderate intermittent working mode can yield violent cavitation effects and avoid undesirable energy dissipation. Nearly a quarter of the saturated crude oil can be recovered from the tight core through ultrasonic-assisted CO2 flooding. It can be attributed to the composition alterations of crude oil and property changes of core matrix. Coupling with ultrasonic waves, CO2 would extract and vaporize crude oil more easily, which promotes oil swelling, lowers oil density and viscosity, decreases oil–gas interfacial tension and thus improves oil recovery. Besides, the ultrasound can help to mitigate the impact of CO2 adsorption-induced clay swelling on pore sizes through fluctuating pressure. And the strong hydrodynamic shear forces generated by mechanical vibration of ultrasound may also help to connect individual small pores and extend micro-fractures. These synergistic effects result in the transformation of micropores into mesopores and macropores. Furthermore, the wettability alteration of core samples implies that the ultrasonic-assisted CO2 flooding can induce the detachment of oil films from the rock surface. Finally, the results of molecular dynamics simulations indicate that the improvement in pressure inside the core sample resulting from ultrasonic cavitation facilitates the mixing of CO2 and oil, thereby weakening gas channeling and improving the displacement efficiency.

Water, environment, and health nexus: understanding the risk factors for waterborne diseases in communities along the Tano River Basin, Ghana.

Freshwater pollution is a major concern in Ghana, directly impacting human health. However, the underlying drivers of exposure and risks are not comprehensively understood, emphasizing the severity and impact of these diseases. This study assessed the interaction between water and human health, specifically focusing on the risk factors for waterborne diseases and the drivers of water pollution among residents near the Tano River Basin, Ghana. A sample size of 400 households was selected from five communities within the basin based on their proximity to the Tano River. In addition, the study combined both spatial and non-spatial data sources to map potential flood zones for the basin. The study found that inadequate sanitation, poor hygiene practices, and contamination from illegal mining were the primary causative factors of waterborne diseases. Additionally, floods and improper waste management significantly contributed to disease outbreaks. The flood susceptibility analysis indicated that areas highly susceptible to flooding cover 21.2% of the basin, predominantly in the southern part. The results highlight the urgent need for comprehensive interventions to address the drivers of waterborne diseases. This study will contribute to the local authorities in developing plans to prevent waterborne diseases and mitigate their economic and public health impacts.

The Importance of Law Enforcement and Spatial Planning Regulations Regarding Flood Management

Spatial planning in Indonesia, both national and regional spatial planning, has become a crucial problem that has developed dynamically in recent years. The urgency of spatial management in human life encourages the existence of statutory regulations to address spatial planning. Spatial planning is an important component in determining the success of a region's development, especially in the context of sustainable development. Rapid regional growth, both in urban and rural areas, has had a positive economic impact, but has also given rise to environmental problems, manifested in increasingly critical environmental conditions and the increasing intensity of natural disasters, partly caused by spatial planning violations. One of the significant impacts of spatial planning violations is flooding in Indonesia, which is often caused by land misuse. Therefore, enforcement of spatial planning laws and regulations closely related to flood management is critical. This study uses a qualitative research approach focusing on literature analysis, government policies, and empirical data related to flood management in Indonesia. Empirical data was obtained through interviews with legal experts, spatial planning experts, and related stakeholders. Deductive methods are used in data analysis to identify patterns and relationships between law enforcement, spatial planning regulations, and flood management. The results of this study show that strict law enforcement, clear spatial regulations, and increasing institutional capacity are the keys to reducing flood risk. With synergy between law enforcement and capacity building, potential flood risks can be minimized while building better community involvement and awareness.

A hydrogeological conceptual model of aquifers in catchments headed by temperate glaciers

Abstract. For reliable forecasting of the evolution of critical water resources, as well as of potential flood and landslide hazards and their response to climate change, it is necessary to improve the understanding and quantification of unknown aquifer systems in glacierized catchments. We focus on four southeastern outlet glaciers of the main Icelandic ice cap, Vatnajökull. A multidisciplinary approach is carried out, including the acquisition of new in situ data to characterize aquifers and their groundwater dynamics. Moreover, the recharge to aquifers from glacial melt and effective rainfall is estimated. From a detailed analysis of all available data and the determination of the dynamic characteristics of the aquifers, a hydrogeological conceptual model of glacierized catchments is constructed: (i) two distinct aquifers, their hydraulic conductivities and their hydrodynamic responses to climate forcing are identified; (ii) a comprehensive water balance for the whole catchment is obtained; (iii) the subglacial recharge to the aquifers is shown to be 4 times higher than in the proglacial area; and (v) the importance of the impact of the glacial melt recharge on the groundwater system is demonstrated. Thus, we highlight the major role that the groundwater component has in the hydrodynamic functioning of glacierized catchments.

Socio-Economic Vulnerability to Potential Flood in Tamakoshi River in Nepal

Tamakoshi, a transboundary river flowing from Tibet, China to Nepal has experienced several disastrous flash floods resulting in the loss of lives, infrastructures, settlements, lands, and other assets. Many households, populations, and public and private properties such as houses, land, roads, bridges, etc. are likely to be affected by the potential flash floods. This study discusses the occurrence of flash floods, losses and damages from such floods in the past, and socio-economic vulnerability to potential flash floods. It further discusses the preparedness and response activities and identifies the measures for flood risk reduction. The methods adopted for data collection included observation, household surveys, and focus group discussions. The villages selected for detailed study are Gongarkhola, Jagat, Jamune, Bhorle, and Sigati bazaar, identified as the most vulnerable settlements along the Tama Koshi River. It is found that flash floods and high-intensity precipitation occur frequently in the study area resulting in loss of life and properties, and people and properties are exposed to the potential flash floods. Local people are still feeling vulnerable to such flash floods. The government authorities alone are not able to achieve greater success in carrying out preparedness and response activities for flood risk reduction without the active involvement and participation of the vulnerable communities. Development and effective implementation of land-use guidelines and building codes, watershed management, early warning systems, and networking among the people residing across the river are some of the activities identified to reduce flood risk. Although people have a good understanding and knowledge about floods and their occurrences, they pay less attention to preparedness and mitigation. It is also concluded that structural measures alone are not sufficient and effective enough for flood risk reduction

Design of Automatic Flood Control System in Kulon Progo, Special Region of Yogyakarta, Indonesia

The construction of Yogyakarta International Airport has resulted in land use changes and increased the topography in the area by up to 9 m, which has led to potential flooding. A spatial analysis was conducted on the flow direction after the airport's construction, specifically in the West Carik watershed. It was discovered that the flow direction was uncertain and trapped upstream of the airport. A polder system with automation is proposed as a solution to the drainage problem. An automation system is designed for pump operation with the objective of improving efficiency. The system is expected to reduce the volume of water in the polder by reducing human involvement and providing ease in monitoring. The results of hydrological analysis with a 50-year return period flood resulted in a design flood discharge of 11.73 m3/s. The polder has a storage capacity of 63,312 m3, a depth of 4 m, and a surface area of 1.58 ha. It requires a total pump capacity of 8.4 m3/s, consisting of three pump units, with one unit having a capacity of 1.8 m3/s and two units with 3.3 m3/s. One additional pump with a capacity of 3.3 m3/s is also planned as a backup pump. The pump automation system simulation employs an Arduino UNO as the controller, water level sensor, and relay. This system successfully fulfills the desired operational system for the pump. In the actual implementation, a Programmable Logic Controller (PLC) is required as the controller, with water level sensors, relays, and contactors as inputs and outputs.

A fuzzy analytical hierarchy process -GIS approach to flood susceptibility mapping in NEOM, Saudi Arabia

The Kingdom of Saudi Arabia is undergoing massive and rapid urbanization as part of Vision 2030. This includes development projects along Saudi Arabia’s coastline across the Red Sea. Coastal areas, especially the ones along Saudi’s western regions are susceptible to natural disasters such as flooding. NEOM, a futuristic city currently being developed in the northwest of Saudi Arabia, exemplifies a potential flooding hazard due to its geographic location and proposed urbanization plans. This research aims to enhance flood hazard assessment in NEOM by applying the Fuzzy Analytical Hierarchy Process (FAHP) in combination with Geographic Information System (GIS). Acknowledging traditional limitations related to data availability and parameter selection consensus, the study carefully selects parameters such as drainage density, elevation, slope, rainfall, land use/land cover (LULC), soil type, normalized difference vegetation index (NDVI), and topographic wetness index (TWI). The 30 m DEM was used to derive Drainage Density, Slope, and TWI while LULC data helped assess land cover changes. Rainfall data and soil type information are integrated to evaluate their impact on flood susceptibility. NDVI is employed to analyze vegetation cover. Utilizing ArcGIS Pro’s weighted overlay model, the criteria were combined to generate the final flood susceptibility map. The research outcomes manifest in a flood susceptibility map categorizing areas into seven distinct susceptibility classes, ranging from ‘very low’ to ‘very high.’ A quantitative breakdown in a summary table provides insights into the proportional distribution of flood risk. Results indicate a significant portion of NEOM falls within varying degrees of moderate susceptibility range with relatively limited distribution of flood susceptibility on the extremes, equating to areas with ‘low to moderate’ susceptibility is 4,322.8 km2, areas with ‘moderate’ susceptibility is 5,109.69 km2, areas with ‘moderate to high’ is 4,081.39 km2. The flood susceptibility map developed in this study can shed insights on potential optimum areas for flood mitigation measures (i.e., optimum locations for establishing stormwater collection points).

The Influence of Land Subsidence on Risk of Constructing 150 kV Transmission Tower for South Sumatra – Bangka Belitung Interconnector

Transmission system is one of the national essential objects and should be reliable when functioning. Moreover, disturbances in transmission system can lead to disruption of the service function. A common risk to the reliability of electric distribution is land subsidence on transmission tower. Furthermore, the 150 KV interconnector of South Sumatra-Bangka Belitung (Sumsel-Babel) is located in the coastal area of Banyuasin Dua sub-district, South Sumatra. This area is a river delta with peat and clay soil structures and is prone to land subsidence. Therefore, this research aimed to identify environmental factors that affect land subsidence and cause risk to transmission tower. In the context of this research, Copras (Complex Proportional Assessment) and MCSA (Multi Criteria Spatial Analysis) were used for parameter weighting and risk assessment of tower location, respectively. The results of an expert survey to assess risk of potential land subsidence at tower location showed five parameters, namely, land use, distance to waters or potential flooding, land slope factor, soil type, and conus value. Individual parameters were weighted quantitatively and qualitatively based on the opinions of construction experts. Specifically, the qualitative method was performed by weighting based on criteria and sub-criteria, which were analyzed using Analytic Hierarchy Process (AHP). On the other hand, spatial analysis of locations at risk of land subsidence was conducted using GIS software. Based on the assessment results obtained, land use criteria had the largest weighting influence of 0.340 and the smallest weighting on the cone value was 0.08. Finally, tower location that are most at risk of land subsidence are on peatland, near water, and clay soil.

Current flood risk management: gaps and perspectives in Stung Sen Catchment, Cambodia

ABSTRACT People who live in Cambodia's flood-prone areas are at a heightened risk of experiencing a flood disaster due to climate change and urbanization. Annual flood disasters have an impact on the Stung Sen River Basin, the largest tributary river of Tonle Sap Lake. Through interviews with pertinent stakeholders, we investigate the current gaps in flood control risk management at the Stung Sen Catchment, the national to local levels. At a common level, the Kampong Kor, Kampong Svay, and Meanchey were selected for the interview and field survey. The findings highlight that a top-down approach is used to alert locals about potential flood danger. The results emphasized the difficulties in addressing cross-border flood warning issues, the effects of incorrect urbanization development and climate change on vulnerable populations, and the inadequate readiness for the safety of children in flood-prone locations. Consequently, we suggest the integrated flood risk management framework as a very effective way to lessen the impact of flood risk for both present and future flood risk harm.

Flood Susceptibility Mapping Using Information Fusion Paradigm Integrated with Decision Trees

Accurate estimation of flood-damaged zones in a watershed is prominent in guiding a framework for developing sustainable strategies. For these purposes, several flood conditioning factor values at flooded and non-flooded points are extracted, and those points are analyzed using decision tree algorithms and eight novel information fusion techniques to get more reliable flood susceptibility mapping. The belief function values of flood susceptibility values at leaf nodes of the tree are fused by several techniques named Dempster-Shafer (DS), Fuzzy Gamma Overlay (FGO), Hesitant Fuzzy Weighted Averaging (HFWA), Hesitant Fuzzy Weighted Geometric (HFWG), Hesitant Fuzzy Weighted Ordered Averaging (HFWOA), HFWOG, Closeness coefficient (Cc) using Euclidean and Manhattan distances. The flood susceptibility values are extracted from the generated maps and are validated by receiver operating characteristics (ROC) curve parameters, and the seed cell area index (SCAI) of classified flood levels. The area under ROC (AUROC) values of training process are 0.997 for DS, HFWA, HFWOA, and Cc-Euclidean, 0.996 for Cc-Manhattan, 0.995 for FGO and 0.994 for HFWG and HFWOG. The AUROC values of the testing process are 0.951 for DS, HFWA, HFWOA, Cc-Euclidean, and Cc-Manhattan, 0.945 for FGO, 0.943 for HFWG, and 0.941 for HFWOG. True Skill Statistics values are 0.962 and 0.870 for training and testing processes. Although these techniques present excellent performance, the SCAI values versus flood susceptibility classes are fitted to assess the prediction capabilities of the techniques further. HFWA and HFWOG have the first- and second-best performances on the estimations. Hence, information fusion paradigm can be employed to combine flood conditioning factors based on a robust classification method to get reliable predictions of flood potential levels and utilize them for land use and construction planning and management.

An assessment of the potential of polymer flooding at an oil field in Western Siberia

An assessment of the potential of polymer flooding at an oil field in Western Siberia

Integration of UH SUH, HEC-RAS, and GIS in Flood Mitigation with Flood Forecasting and Early Warning System for Gilireng Watershed, Indonesia

A flood forecasting and early warning system is critical for rivers that have a large flood potential, one of which is the Gilireng watershed, which floods every year and causes many losses in Wajo Regency, Indonesia. This research also introduces an integration model between UH SUH and HEC-RAS in flood impact analysis, as a reference for flood forecasting and early warning systems in anticipating the timing and occurrence of floods, as well as GIS in the spatial modeling of flood-prone areas. Broadly speaking, this research is divided into four stages, namely, a flood hydrological analysis using UH SUH, flood hydraulic tracing using a 2D HEC-RAS numerical model, the spatial modeling of flood-prone areas using GIS, and the preparation of flood forecasting and early warning systems. The results of the analysis of the flood forecasting and early warning systems obtained the flood travel time and critical time at the observation point, the total time required from the upstream observation point to level 3 at Gilireng Dam for 1 h 35 min, Mamminasae Bridge for 4 h 35 min, and Akkotengeng Bridge for 8 h 40 min. This is enough time for people living in flood-prone areas to evacuate to the 15 recommended evacuation centers.

Contribution of Mesoscale Convective Systems to Floods in the East Asian Summer Monsoon Region

AbstractThe quantitative relationship between Mesoscale Convective Systems (MCSs) and floods over East Asia has not been established. In this study, MCSs are clustered into four types with Self‐Organizing Map approach. Floods in June‐August of 2000–2021 are linked with different types of MCS by automated algorithms we constructed. We find that among the major floods (potential flood peak periods), 91% (87%) are related to MCS, 65% (78%) are dominated by MCS, and 38% (20%) are dominated by multi‐types of MCS. Types 1 and 2 MCS have higher flood‐inducing efficiencies than common MCS (Type‐4). Type‐1 MCS, characterized by the least number (2% of the total number), the largest precipitation volume, longest lifetime, slowest moving, strongest precipitation, can most efficiently produce floods. Type‐2 MCS, characterized by the second largest precipitation volume, more numerous than Type‐1 particularly over land, can induce floods not only relatively efficiently but also more frequently than Type‐1.

Cropland inundation mapping in a mountain dominated region based on multi-resolution remotely sensed imagery and active learning for semantic segmentation

Accurate and timely mapping of cropland inundated area is critical to loss assessment and recovery plan development. However, existing methods for cropland inundation mapping using Synthetic Aperture Radar (SAR) imagery are primarily designed for plain regions and may not be suitable for mountainous regions. The complex rugged terrain at large scale present challenges such as significant noise from radar shadows, smooth surfaces, floodplains, and permanent water bodies. To remove these noise for effectively mapping of cropland inundation, this study proposes a robust two-stage framework integrating the multi-resolution remotely sensed imageries and semantic segmentation method. First, active learning for cropland extraction is performed with Google Very-High-Resolution (VHR) imagery and Segformer model. Second, the cropland inundation area is obtained using marker-controlled watershed segmentation (MCW) on Sentinel-1 SAR imagery with area-of-interest (AOI) filtering. Results show that the extracted cropland mask are superior to six public cropland data products including ESA, ESRI, FCS30, FROM, GL30, and SLOPE. In addition, with AOI filtering, the F-score of the potential flood identification using MCW was increased from 0.685 to 0.828. At last, the monthly cropland inundation caused by intense rainfall varied approximately from 6.6 km2 to 436.1 km2 during monsoon season of 2017–2022 in Guangdong. Our approach offers a fast and feasible solution for mapping cropland inundation in large and complex mountainous regions, without requiring extensive parameter tuning or additional data.

Evaluation of potentially susceptible flooding areas leveraging geospatial technology with multicriteria decision analysis in Edo State, Nigeria

Floods have claimed lives and devastated societal and ecological systems. Because of their catastrophic tendency and the financial and fatalities they cause, floods have become more and more significant on a global scale in recent years. In Edo State, Nigeria, flooding is a frequent threat that happens annually and seriously damages both lives and property. While the potential of flooding cannot entirely be eliminated, geospatial-based technologies can greatly lessen its effects. In Nigeria's flood-prone Edo State, the study's objectives are to identify inundated places and provide nuanced mapping of the flood risk. To facilitate the determination of the flood risk index (FRI), the study's fundamental flood-predictive features were determined by taking into consideration elevation, slope, distance from the river, rainfall intensity, land use/land cover, soil texture, topographic roughness index, topographic wetness index, normalized difference vegetation index (NDVI), runoff coefficient, aspect, drainage capacity, flow accumulation, the sediment transport index, and the stream power index. The significance of each predictive factor in the analytic hierarchy procedure (AHP) was determined by gathering expert views and perspectives from public entities. A flood threat map was created by processing the gathered data using the AHP and the ArcGIS 10.5 framework. The multicollinearity (MC) estimation was applied to assess the model's predictability. The results of the FRI showed that there were high and extremely severe flood risk zones that affected roughly 26 and 9% of the area, respectively. Flood risks have been identified as predominant in the Edo south region of the study area, which is characterized by low elevation and slope, high drainage capacity, distance from the river, topographic wetness, and index. It showed that the model's resultant vulnerability to flooding maps agreed with past flood occurrences that were previously experienced in the research area, demonstrating the technique's efficacy in locating and mapping locations plagued by flooding. Linear regression (R2) analysis was further conducted on the FRI to evaluate the scientific reliability of the utilized methodology; this shows 0.816 (81.6%) dependability. Consequently, frequent and long-lasting implementation of flooding predictions, warning systems, and mitigation strategies may be achieved.

Integrated flood hazard assessment using multi-criteria analysis and geospatial modeling

Floods are one of the most prevalent disasters worldwide, including in the capital city of Indonesia. Multi-criteria decision analysis is combined with Geographic Information Systems to produce a mapping of flood hazard areas. The weighting for each parameter is based on six criteria: rainfall, slope gradient, topography, soil type, land cover, and distance from rivers. The flood hazard map is validated using inundation data from the Regional Disaster Management Agency for the years 2015 and 2020. From the general analysis, it can be determined that the parameter most influencing floods is rainfall with a weight of 0.270, followed by slope gradient at 0.164, topography at 0.124, soil type at 0.096, land cover at 0.190, and distance from rivers at 0.155. Therefore, through mapping using QGIS, it is revealed that in 2002, highly flood hazard areas comprised 20.99% of the total Ciliwung Watershed area, which increased to 24.31% in 2020. The validation of the flood hazard map was conducted by recording the coordinate points of flood incidents in 2015 and 2020, revealing that the affected areas within the Ciliwung Watershed occurred in high to very high vulnerability zones. This research demonstrates that flood events in the study area occurred in high to very high flood hazard zones. The results of this study are considered valuable and important for providing accurate information to local governments to develop cost-effective and efficient strategies in dealing with potential flood hazards.